Voice and speech recognition for call center feedback and quality assurance

ABSTRACT

A computer-implemented method for providing an objective evaluation to a customer service representative regarding his performance during an interaction with a customer may include receiving a digitized data stream corresponding to a spoken conversation between a customer and a representative; converting the data stream to a text stream; generating a representative transcript that includes the words from the text stream that are spoken by the representative; comparing the representative transcript with a plurality of positive words and a plurality of negative words; and generating a score that varies according to the occurrence of each word spoken by the representative that matches one of the positive words, and/or the occurrence of each word spoken by the representative that matches one of the negative words. Tone of voice, as well as response time, during the interaction may also be monitored and analyzed to adjust the score, or generate a separate score.

RELATED APPLICATIONS

The current patent application is a continuation of, and claims thebenefit of, U.S. patent application Ser. No. 16/150,699, filed Oct. 3,2018 and entitled “VOICE AND SPEECH RECOGNITION FOR CALL CENTER FEEDBACKAND QUALITY ASSURANCE,” which is a continuation of U.S. patentapplication Ser. No. 15/823,850, entitled “VOICE AND SPEECH RECOGNITIONFOR CALL CENTER FEEDBACK AND QUALITY ASSURANCE,” filed Nov. 28, 2017(now U.S. Pat. No. 10,122,855), which is a continuation patentapplication which claims priority benefit with regard to all commonsubject matter to U.S. patent application Ser. No. 15/409,188, entitled“VOICE AND SPEECH RECOGNITION FOR CALL CENTER FEEDBACK AND QUALITYASSURANCE,” filed Jan. 18, 2017, now U.S. Pat. No. 9,871,918, whichclaims priority benefit with regard to all common subject matter to U.S.patent application Ser. No. 15/091,121, now U.S. Pat. No. 9,596,349,entitled “VOICE AND SPEECH RECOGNITION FOR CALL CENTER FEEDBACK ANDQUALITY ASSURANCE,” filed Apr. 5, 2016 which claims priority benefitwith regard to all common subject matter to U.S. Provisional ApplicationSer. No. 62/186,145, entitled “VOICE AND SPEECH RECOGNITION FOR CALLCENTER FEEDBACK AND QUALITY ASSURANCE,” filed Jun. 29, 2015. The listed,earlier-filed applications are hereby incorporated by reference in theirentireties into the current patent application.

FIELD OF THE INVENTION

The present disclosure generally relates to computing devices, softwareapplications, and methods that utilize voice and speech recognition toprovide feedback to a customer service representative regarding hisperformance during an interaction with a customer.

BACKGROUND

Recorded phone conversations between a customer calling a call centerand a customer service representative are often utilized to evaluate theperformance of the representative. A supervisor of the representative ormanager may listen to at least a portion of one or more conversations inorder to check for behavior that needs improvement, such as interruptingthe customer, using improper language, using an inappropriate tone ofvoice, or the like. The supervisor may also listen for following properprotocols, positive interactions with customers, and behavior thatshould be rewarded and reinforced. However, in many cases, long periodsof time may go by between the recorded conversations and the opportunityfor the supervisor to listen to them. During this time, bad behavior ofthe representative may go uncorrected while positive actions may beunrecognized, leading to development of habits that are difficult tochange.

BRIEF SUMMARY

Embodiments of the present technology relate to computing devices,software applications, computer-implemented methods, andcomputer-readable media for providing an evaluation to a customerservice representative regarding his performance during an interactionwith a customer. The embodiments may provide for receiving a data streamcorresponding to a spoken conversation between a customer and arepresentative, generating a representative transcript from theconversation, comparing the representative transcript to a list ofpositive words and negative words, determining tone of voicecharacteristics from the representative and the customer, determining aresponse time between when the customer stops speaking and therepresentative starts speaking, and/or generating one or more scoresthat vary according to the representative's word usage, tone of voice,and response time.

In a first aspect, a computer-implemented method for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Themethod may include: (1) receiving a digitized data stream correspondingto a spoken conversation between a customer and a representative; (2)converting the data stream to a text stream; (3) generating arepresentative transcript that includes the words from the text streamthat are spoken by the representative; (4) comparing the representativetranscript with a plurality of positive words and a plurality ofnegative words; and/or (5) generating a score that varies according tothe occurrence of each word spoken by the representative that matchesone of the positive words and the occurrence of each word spoken by therepresentative that matches one of the negative words to facilitate anobjective evaluation of a customer interaction. The method may includeadditional, fewer, or alternative actions, including those discussedelsewhere herein, and/or may be implemented via one or more processorsand/or via computer-executable instructions stored on non-transitorycomputer-readable medium or media.

In another aspect, a computing device for providing an evaluation to acustomer service representative regarding his performance during aninteraction with a customer may be provided. The computing device mayinclude a memory element and a processing element. The processingelement may be electronically coupled to the memory element. Theprocessing element may be configured to receive a digitized data streamcorresponding to a spoken conversation between a customer and arepresentative, convert the data stream to a text stream, generate arepresentative transcript that includes the words from the text streamthat are spoken by the representative, compare the representativetranscript with a plurality of positive words and a plurality ofnegative words, and/or generate a score that varies according to theoccurrence of each word spoken by the representative that matches one ofthe positive words and the occurrence of each word spoken by therepresentative that matches one of the negative words to facilitate anobjective evaluation of a customer interaction. The computing device mayinclude additional, fewer, or alternate components and/or functionality,including those discussed elsewhere herein.

In yet another aspect, a software application for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Thesoftware application may comprise a speech recognition component, atranscript comparison component, and a score generator. The speechrecognition component may receive a digitized data stream correspondingto a spoken conversation between a customer and a representative. Thespeech recognition component may be configured to convert the datastream to a text stream and generate a representative transcript thatincludes the words from the text stream that are spoken by therepresentative. The transcript comparison component may receive therepresentative transcript. The transcript comparison component may beconfigured to compare the representative transcript with a plurality ofpositive words and a plurality of negative words, determine a positivecount corresponding to a number of occurrences when the words of therepresentative transcript match one or more positive words, and/ordetermine a negative count corresponding to a number of occurrences whenthe words of the representative transcript match one or more negativewords. The score generator may receive the positive count and thenegative count. The score generator may be configured to generate ascore which varies based upon the positive count and the negative countto facilitate an objective evaluation of a customer interaction. Thesoftware application may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In yet another aspect, a computer-readable medium for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Thecomputer-readable medium may include an executable program storedthereon, wherein the program instructs a processing element of acomputing device to perform the following steps: (1) receiving adigitized data stream corresponding to a spoken conversation between acustomer and a representative; (2) converting the data stream to a textstream; (3) generating a representative transcript that includes thewords from the text stream that are spoken by the representative; (4)comparing the representative transcript with a plurality of positivewords and a plurality of negative words; and/or (5) generating a scorethat varies according to the occurrence of each word spoken by therepresentative that matches one of the positive words and the occurrenceof each word spoken by the representative that matches one of thenegative words to facilitate an objective evaluation of a customerinteraction. The program stored on the computer-readable medium mayinstruct the processing element to perform additional, fewer, oralternative actions, including those discussed elsewhere herein.

Advantages of these and other embodiments will become more apparent tothose skilled in the art from the following description of the exemplaryembodiments which have been shown and described by way of illustration.As will be realized, the present embodiments described herein may becapable of other and different embodiments, and their details arecapable of modification in various respects. Accordingly, the drawingsand description are to be regarded as illustrative in nature and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of computing devices,software applications, and computer-implemented methods disclosedtherein. It should be understood that each Figure depicts an embodimentof a particular aspect of the disclosed computing devices, softwareapplications, and computer-implemented methods, and that each of theFigures is intended to accord with a possible embodiment thereof.Further, wherever possible, the following description refers to thereference numerals included in the following Figures, in which featuresdepicted in multiple Figures are designated with consistent referencenumerals. The present embodiments are not limited to the precisearrangements and instrumentalities shown in the Figures.

FIG. 1 illustrates an exemplary environment, shown in block schematicform, in which various components of a computing device may be utilized,the computing device configured to provide an evaluation to a customerservice representative regarding his performance during an interactionwith a customer;

FIGS. 2A and 2B illustrate at least a portion of the steps of anexemplary computer-implemented method for providing an evaluation to acustomer service representative regarding his performance during aninteraction with a customer; and

FIG. 3 illustrates various components of an exemplary softwareapplication shown in block schematic form, the software applicationconfigured to provide an evaluation to a customer service representativeregarding his performance during an interaction with a customer.

The Figures depict exemplary embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the systems and methodsillustrated herein may be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION

The present embodiments described in this patent application and otherpossible embodiments may relate to, inter alia, computing devices,software applications, methods, and media for providing an evaluation toa customer service representative regarding his performance during aninteraction with a customer. The computing device, through hardwareoperation, execution of the software application, implementation of themethod, or combinations thereof, may be utilized as follows. An existingcustomer, or a potential customer, may call a business seekinginformation regarding one or more products or services offered by thebusiness, seeking to discuss a bill or an account, seeking to changeservices or return a product, or the like. The representative may answerthe call with a telecom device, such as a telephone including a headsetor a handset. The representative may have a conversation with thecustomer to provide information or resolve the customer's issue. Thecomputing device may also receive the call either through acommunication line, such as a phone line, or through a connection withthe telecom device.

The computing device may have already been trained to recognize oridentify the representative's voice. While the customer and therepresentative are talking, the computing device may be tracking, orcontinuously determining, which voice is that of the representative. Thecomputing device may also determine the voice which is not recognized,or already known, is that of the customer. The computing device may alsoperform speech recognition, converting the dialog between the customerand the representative to text. The computing device may identify wordsof the text that are spoken by the representative and may compare thewords with a list of positive words or phrases and a list of negativewords or phrases. The positive words or phrases may include languagethat is preferred for interacting with customers, such as correctgrammar, common courtesies, and proper etiquette. The negative words orphrases may include language that is considered to be incorrect grammar,slang, or obscenities. The computing device may generate a first scorefor the representative's customer service performance. The first scoremay vary according to the usage of positive words and negative words bythe representative. For example, the first score may increase when therepresentative uses positive words or phrases. Likewise, the first scoremay decrease when the representative uses negative words or phases.

In addition, the computing device may analyze the conversation todetermine a tone of voice for the representative and to determine a toneof voice for the customer. The tone of voice of the representative andthe customer may refer to the frequency or spectral content of eachone's voice. The tone of voice may also refer to the amplitude or volumeof each voice. The tone of voice for the representative and the customermay be determined and recorded during the entire conversation. Thus, theresponses of the representative to the customer can be determined. Inother words, it may be determined whether the representative changed histone of voice in response to a change in tone of voice of the customer.The computing device may generate a second score that varies accordingto the responses of the representative to the customer. For example, thesecond score may increase for every time that the customer changed histone of voice and the representative did not. Likewise, the second scoremay decrease for every time that the representative changed his tone ofvoice in response to a change in tone of voice of the customer. Thesecond score may be combined with the first score, such as by additionof the two scores or averaging of the two scores.

Furthermore, the computing device may determine when a change ofspeakers occurs during the conversation—that is when the customer stopstalking and the representative starts talking. The computing device mayfurther determine a response time which is related to the period of timethat elapses between when the customer stops talking and therepresentative starts talking. The computing device may generate a thirdscore that varies according to the response time. For example, there maybe a window of time, say between a lower threshold of 1 second and anupper threshold of 5 seconds, during which it is considered polite forthe representative to respond to the customer. If the response time isless than the lower threshold or the representative and the customer arespeaking simultaneously, then the representative may be interrupting thecustomer. If the response time is greater than the upper threshold, thenthe representative may be considered to be keeping the customer waiting.In an exemplary implementation, the third score may not change as longthe response time is within the window. But, the third score maydecrease for every occurrence when the response time is less than thelower threshold or greater than the upper threshold. The third score maybe combined with the first and second scores, such as by addition of thethree scores or averaging of the three scores.

After the phone call between the representative and the customer isover, the computing device may present the representative with a totalscore that represents the combination of the three individual scores. Inaddition or instead, the computing device may present the representativewith the three individual scores. Furthermore, the computing device maypresent the representative with a summary of the evaluation. The summarymay include a list of both the positive words or phrases, and thenegative words and phrases, used by the representative. The summary mayalso include a list of occurrences when the representative changed histone of voice, and the times during the conversation when they occurred.The summary may further include a list of occurrences when therepresentative did not respond to the customer during the window of timefor a proper response, and the times during the conversation when theyoccurred. The evaluation may further include suggestions for improvementor behavioral changes, if needed.

Specific embodiments of the technology will now be described inconnection with the attached drawing figures. The embodiments areintended to describe aspects of the invention in sufficient detail toenable those skilled in the art to practice the invention. Otherembodiments can be utilized and changes may be made without departingfrom the scope of the present invention. The following detaileddescription is, therefore, not to be taken in a limiting sense. Thescope of the present invention is defined only by the appended claims,along with the full scope of equivalents to which such claims areentitled.

Exemplary Computing Device

FIG. 1 depicts an exemplary environment in which embodiments of acomputing device 10 may be utilized. The environment may include acommunication network 12, a customer telecom device 14, a representativetelecom device 16, and/or a display 18. The computing device 10 maybroadly comprise a memory element 20 and a processing element 22 capableof executing a software application 24. The computing device 10 mayprovide an evaluation to a customer service representative regarding hisperformance during an interaction with a customer. Examples of thecomputing device 10 may include a workstation computer, a desktopcomputer, a laptop computer, a palmtop computer, a tablet computer, asmart phone, other type of mobile device, wearable electronics, smartwatch, or the like. In various embodiments, the computing device 10 andthe representative telecom device 16 may be integrated with one another.

The communication network 12 generally allows communication between thecustomer telecom device 14 and the representative telecom device 16. Thecommunication network 12 may include local area networks, metro areanetworks, wide area networks, cloud networks, the Internet, cellularnetworks, plain old telephone service (POTS) networks, and the like, orcombinations thereof. The communication network 12 may be wired,wireless, or combinations thereof and may include components such asmodems, gateways, switches, routers, hubs, access points, repeaters,towers, and the like. The telecom devices 14, 16 may connect to thecommunication network 12 either through wires, such as electrical cablesor fiber optic cables, or wirelessly, such as RF communication usingwireless standards such as cellular 2G, 3G, or 4G, Institute ofElectrical and Electronics Engineers (IEEE) 802.11 standards such asWiFi, IEEE 802.16 standards such as WiMAX, Bluetooth™, or combinationsthereof.

The customer telecom device 14 generally allows the customer tocommunicate with the representative of the business. The customertelecom device 14 may be embodied by a cell phone, a mobile phone, asmart phone, a landline, or any phone or electronic device capable ofsending and receiving voice communication through the communicationnetwork 12. The customer telecom device 14 may include electroniccircuitry to send and receive voice communication either wirelessly orthrough wires or cables. The customer telecom device 14 may furtherinclude user interface components such as a keypad, a speaker and amicrophone incorporated in a headset or handset, and the like. Thecustomer may utilize the customer telecom device 14 in a conventionalmanner.

The representative telecom device 16 generally allows the representativeto communicate with the customer. The representative telecom device 16may be typically embodied by a landline type of phone including a basestation and a headset with a microphone and a speaker, although othertypes of phones, such as a smart phone, may be utilized. Therepresentative telecom device 16 may function in a substantially similarfashion to the customer telecom device 14 such that the representativetelecom device 16 may communicate with the customer telecom device 14through the communication network 12 to allow the representative to havea conversation with the customer.

The display 18 generally presents information to the representative. Thedisplay 18 may include video devices of the following types: plasma,light-emitting diode (LED), organic LED (OLED), Light Emitting Polymer(LEP) or Polymer LED (PLED), liquid crystal display (LCD), thin filmtransistor (TFT) LCD, LED side-lit or back-lit LCD, heads-up displays(HUDs), or the like, or combinations thereof. The display 18 may includea screen on which the information is presented, with the screenpossessing a square or a rectangular aspect ratio that may be viewed ineither a landscape or a portrait mode. In various embodiments, thedisplay 18 may also include a touch screen occupying the entire screenor a portion thereof so that the display 18 functions as part of a userinterface. In some embodiments, the display 18 may be housed in amonitor housing or the like. In other embodiments, the display 18 may beintegrated with the computing device 10.

The memory element 20 may include data storage components such asread-only memory (ROM), programmable ROM, erasable programmable ROM,random-access memory (RAM) such as static RAM (SRAM) or dynamic RAM(DRAM), cache memory, hard disks, floppy disks, optical disks, flashmemory, thumb drives, universal serial bus (USB) drives, or the like, orcombinations thereof. In some embodiments, the memory element 20 may beembedded in, or packaged in the same package as, the processing element22. The memory element 20 may include, or may constitute, a“computer-readable medium.” The memory element 20 may store theinstructions, code, code segments, software, firmware, programs,applications, apps, services, daemons, or the like, including thesoftware application 24, that are executed by the processing element 22.

The processing element 22 may include processors, microprocessors(single-core and multi-core), microcontrollers, digital signalprocessors (DSPs), field-programmable gate arrays (FPGAs), analog and/ordigital application-specific integrated circuits (ASICs), or the like,or combinations thereof. The processing element 22 may generallyexecute, process, or run instructions, code, code segments, software,firmware, programs, applications, apps, processes, services, daemons, orthe like. The processing element 22 may also include hardware componentssuch as finite-state machines, sequential and combinational logic, andother electronic circuits that may perform the functions necessary forthe operation of the current invention. The processing element 22 mayfurther include, or be in electronic communication with, circuitry todecode or convert wireless signals, as well as sampling circuits, analogto digital converters (ADCs), filtering circuits, amplifier circuits,and the like. The processing element 22 may be in communication with theother electronic components through serial or parallel links thatinclude address buses, data buses, control lines, and the like.

By executing the software application 24 or through the use ofspecially-configured hardware, the processing element 22 may perform thefollowing tasks. Before the computing device 10 is utilized during aphone call, the processing element 22 may be trained to recognize oridentify the representative's voice. The training process may involvehaving the representative utilize the representative telecom device 16as a microphone into which the representative speaks. The representativetelecom device 16 may communicate an audio signal to the computingdevice 10. The audio signal may be digitized and optionally filtered toeliminate noise and frequencies outside of the typical human vocal rangeby the representative telecom device 16 and/or the computing device 10to create a data signal received by the processing element 22.Alternatively, the representative may utilize a standalone microphoneelectrically connected to the computing device 10, a microphone from aheadset electrically connected to the computing device 10, or amicrophone integrated with the computing device 10 to generate the audiosignal. The representative may speak a plurality of words or phrases ora series of sounds which are analyzed by the processing element 22 tocreate a voice print, template, or model that is stored in the memoryelement 20. The processing element 22 may generate a spectrogram orutilize short-time Fourier transform to create the voice print. Thevoice print may be used to identify the representative.

During the phone call between the customer and the representative, theprocessing element 22 may receive an audio stream corresponding to thespoken conversation from either the communication network 12 or therepresentative telecom device 16. The audio stream may be digitized andfiltered, in a similar fashion as mentioned above, to create a datastream. The processing element 22 may implement speech recognition ormay convert speech to text utilizing techniques such as hidden Markovmodels, dynamic time warping, neural networking, or the like, orcombinations thereof. The output of the speech recognition may be astream of text words. In various embodiments, the processing element 22may also successively or repeatedly generate a spectrogram or utilizeshort-time Fourier transform to create a plurality of voice prints, eachvoice print representing a short period of time, such as 0.5-1 seconds.The processing element 22 may further compare each voice print with thevoice print of the representative in order to identify the voice of thecurrent speaker during the conversation on an ongoing basis or as afunction of time. Those voice prints that match the voice print of therepresentative may be marked or noted as the voice of therepresentative. Those voice prints that do not match the voice print ofthe representative may be marked or noted as the voice of the customer.The processing element 22 may also timestamp the text so that each wordis associated with a time of the conversation. The processing element 22may match each word of the conversation with one or more voice prints sothat it may determine which person spoke each word. Thus, the processingelement 22 may generate a representative transcript of the conversationwhich includes those words of the text that are spoken by therepresentative. The processing element 22 may also generate a customertranscript including words of the text that are spoken by the customer.

The processing element 22 may compare the representative transcript inan ongoing process throughout the conversation with a list of positivewords or phrases and a list of negative words or phrases. The positivewords or phrases may include language that is preferred for interactingwith customers, such as correct grammar, common courtesies, and/orproper etiquette. The negative words or phrases may include languagethat is considered to be incorrect grammar, slang, and/or obscenities.

The processing element 22 may generate a first score for therepresentative's customer service performance. The first score may varyaccording to the usage of positive words and negative words by therepresentative. For example, the first score may have an initial value,such as 0 or 100. The processing element 22 may increase the first scoreduring the conversation when the representative uses positive words orphrases. Likewise, the processing element 22 may decrease the firstscore when the representative uses negative words or phrases. Theprocessing element 22 may also store in the memory element 20 all of thepositive words used by the representative and the number of occurrencesof each usage, as well as the negative words used by the representativeand the number of occurrences of each usage. In some embodiments, theprocessing element 22 may mark the positive words and negative words inthe representative transcript which is stored in the memory element 20.As an alternative scoring method, the processing element 22 may countthe total number of positive words and negative words and adjust thefirst score accordingly at the end of the phone conversation.

The processing element 22 may also analyze the conversation to determinea tone of voice for the representative and to determine a tone of voicefor the customer. The tone of voice of the representative and thecustomer may refer to the frequency or spectral content of each one'svoice. The tone of voice may also refer to the amplitude or volume ofeach voice. Thus, the processing element 22 may perform mathematical orsignal processing operations such as Fourier transforms, pulse coding,and the like in order to determine variations in the frequency, theamplitude, or both of each voice. The processing element 22 mayrepeatedly generate voice prints and compare them with already storedvoice prints, as discussed above, to identify the voice of therepresentative and the voice of the customer. The processing element 22may further utilize the identities of the voice prints to determine thetone of voice for the representative and the tone of voice for thecustomer on an ongoing basis for the entire conversation. The tone ofvoice of each person may be recorded in the memory element 20 as one ormore values representing the tone of voice for each of a plurality oftimestamps. The tone of voice may be recorded at a given rate, such as1-10 samples per second. Thus, the memory element 20 may include a firstseries of tone of voice values for the representative and a secondseries of tone of voice values for the customer. The processing element22 may also determine a first average tone of voice value for therepresentative and a second average tone of voice value for thecustomer. In addition, the processing element 22 may match, or otherwiseassociate, the tone of voice of the representative with the words spokenby the representative. For example, each word of the conversation spokenby the representative may be associated with an average, or maximum,tone of voice value that was recorded for the particular word of theconversation. The processing element 22 may perform the same operationfor the tone of voice of the customer.

During the conversation, the customer may speak for a turn and then therepresentative may speak for a turn. The representative may respond to aquestion from the customer or may make a statement following a statementfrom the customer. Each turn may correspond to a set of timestamp valuesand the associated tone of voice values for the speaker during the turn.The processing element 22 may determine whether the customer changed histone of voice during his turn and whether the representative changed histone of voice in response. In various embodiments, the processingelement 22 may determine each occurrence when the customer's tone ofvoice value is above a first threshold, such as 10% greater than hisaverage tone of voice value. The processing element 22 may furtherdetermine whether the tone of voice value for the representativeincreases above a second threshold, such as a 10% increase greater thanhis average tone of voice value, within a first time period afterward,such as 10 seconds.

The processing element 22 may generate a second score for therepresentative's customer service performance. The second score may varyaccording to whether the representative changed his tone of voice inresponse to a change in tone of voice of the customer. For example, likethe first score, the second score may have an initial value, such as 0or 100. The processing element 22 may increase the second score duringthe conversation when the representative does not change his tone ofvoice in response to a change in tone of voice of the customer. This mayindicate that the representative has remained calm during a tense orconfrontational moment of the conversation. Likewise, the processingelement 22 may decrease the second score during the conversation whenthe representative changes his tone of voice in response to a change intone of voice of the customer—perhaps indicating that the representativewas unable to remain calm when the customer got agitated.

The processing element 22 may determine when a change of speakers occursduring the conversation—that is when the customer stops talking and therepresentative starts talking. The processing element 22 may repeatedlygenerate voice prints and compare them with already stored voice prints,as discussed above, to identify the voice of the representative and thevoice of the customer. The processing element 22 may further determine aresponse time which is related to the period of time that elapsesbetween when the customer stops talking and the representative startstalking. In certain embodiments, the processing element 22 may start atimer at the end of every word spoken by the customer. The timer maystop when the next word is spoken. If the next word is spoken by therepresentative, then the processing element 22 may record the value ofthe timer—which would correspond to the response time. In some cases,the processing element 22 may determine that the representative and thecustomer are speaking at the same time.

The processing element 22 may generate a third score that variesaccording to the response time. For example, like the first and secondscores, the third score may have an initial value, such as 100. Invarious embodiments, there may be a window of time, say between a lowerthreshold of 1 second and an upper threshold of 5 seconds, during whichit is considered polite for the representative to respond to thecustomer. If the response time is less than the lower threshold or therepresentative and the customer are speaking simultaneously, then therepresentative may be interrupting the customer. If the response time isgreater than the upper threshold, then the representative may beconsidered to be keeping the customer waiting. The processing element 22may record all of the occurrences when the response time was outside ofthe window and the times during the conversation when they occurred. Inan exemplary implementation, the third score may not change as long theresponse time is within the window. But, the processing element 22 maydecrease the third score for every occurrence when the response time isless than the lower threshold, or greater than the upper threshold.

After the conversation has concluded, the processing element 22 maygenerate a total score, which may be a combination of the first, second,and third scores, such as the sum of the three or the average of thethree. In addition or instead, the processing element 22 may present therepresentative with the three individual scores. Furthermore, theprocessing element 22 may present the representative with theevaluation. The evaluation may include a list of both the positive wordsor phrases and the negative words and phrases used by therepresentative. The evaluation may also include a list of occurrenceswhen the representative changed his tone of voice and the times duringthe conversation when they occurred. The evaluation may further includea list of occurrences when the representative did not respond to thecustomer during the window of time for a proper response, and the timesduring the conversation when they occurred. The evaluation mayadditionally include suggestions for improvement or behavioral changes,if needed.

The computing device 10 may be electrically connected to thecommunication network 12 and to the display 18, with an optionalconnection to the representative telecom device 16, as shown in FIG. 1 .During the conversation between the representative and the customer, thecomputing device 10 may receive the audio stream from the communicationnetwork 12 or alternatively from the representative telecom device 16.The processing element 22 may perform the operations necessary toevaluate the representative's customer service performance, as discussedabove. After the conversation is over, the computing device 10 maycommunicate the total score or the first, second, and third scores alongwith the summary of the evaluation to the display 18 so that therepresentative can review the evaluation. Given the immediate feedbackthat the current invention provides, the representative may startaddressing the areas that need improvement before his next phone call.Furthermore, the scores and all of the data recorded during theconversation may be transferred from the memory element 20 of thecomputing device 10 to a data server that is accessible by thesupervisor or manager of the representative.

Exemplary Computer-Implemented Method

FIGS. 2A and 2B depict a listing of steps of an exemplarycomputer-implemented method 100 for providing an evaluation to acustomer service representative regarding his performance during aninteraction with a customer. The steps may be performed in the ordershown in FIGS. 2A and 2B, or they may be performed in a different order.Furthermore, some steps may be performed concurrently as opposed tosequentially. In addition, some steps may be optional. The steps of thecomputer-implemented method 100 may be performed by the computing device10 through the utilization of hardware, software, firmware, orcombinations thereof.

Referring to step 101, data corresponding to words spoken by arepresentative is received. The representative may utilize therepresentative telecom device 16 as a microphone into which therepresentative speaks. The representative telecom device 16 maycommunicate an audio signal to the computing device 10. The audio signalmay be digitized and optionally filtered to eliminate noise andfrequencies outside of the typical human vocal range by therepresentative telecom device 16 and/or the computing device 10 tocreate a data signal received by the processing element 22.

Referring to step 102, a voice print that is associated with therepresentative may be created. The words, phrases, or sounds spoken bythe representative may be analyzed by the processing element 22 tocreate a voice print, template, or model that is stored in the memoryelement 20. The processing element 22 may generate a spectrogram orutilize short-time Fourier transform to create the voice print.

Referring to step 103, a stream of data corresponding to a spokenconversation between a representative and a customer may be received.The stream of data may be received from the communication network 12 orthe representative telecom device 16 as an audio stream which is thendigitized and filtered.

Referring to step 104, a portion of the data may be converted to arepresentative transcript. The processing element 22 may implementspeech recognition or may convert speech to text utilizing techniquessuch as hidden Markov models, dynamic time warping, neural networking,or the like, or combinations thereof. The output of the speechrecognition may be a stream of text words. In various embodiments, theprocessing element 22 may also successively or repeatedly generate aspectrogram or utilize a short-time Fourier transform to create aplurality of voice prints, each voice print representing a short periodof time, such as 0.5-1 seconds. The processing element 22 may furthercompare each voice print with the voice print of the representative inorder to identify the voice of the current speaker during theconversation on an ongoing basis or as a function of time. Those voiceprints that match the voice print of the representative may be marked ornoted as the voice of the representative. Those voice prints that do notmatch the voice print of the representative may be marked or noted asthe voice of the customer. The processing element 22 may also timestampthe text so that each word is associated with a time of theconversation. The processing element 22 may match each word of theconversation with one or more voice prints so that it may determinewhich person spoke each word. Thus, the processing element 22 maygenerate the representative transcript of the conversation. Theprocessing element 22 may also generate a customer transcript.

Referring to step 105, the representative transcript may be compared toa list of positive words or phrases and a list of negative words orphrases. The positive words or phrases may include language that ispreferred for interacting with customers, such as correct grammar,common courtesies, and proper etiquette. The negative words or phrasesmay include language that is considered to be incorrect grammar, slang,and/or obscenities. The comparison of the representative transcript tothe list of positive words and negative words may be performed as anongoing process throughout the conversation.

Referring to steps 106-108, a first score that varies according to theusage of positive words and negative words by the representative may begenerated. For example, the first score may have an initial value, suchas 0 or 100. The processing element 22 may increase the first scoreduring the conversation when the representative uses positive words orphrases. Likewise, the processing element 22 may decrease the firstscore when the representative uses negative words or phases. Theprocessing element 22 may also store in the memory element 20 all of thepositive words used by the representative and the number of occurrencesof each usage as well as the negative words used by the representativeand the number of occurrences of each usage. In some embodiments, theprocessing element 22 may mark the positive words and negative words inthe representative transcript which is stored in the memory element 20.As an alternative scoring method, the processing element 22 may countthe total number of positive words and negative words, and adjust thefirst score accordingly at the end of the phone conversation.

Referring to step 109, a tone of voice for the representative and a toneof voice for the customer may be determined. The tone of voice of therepresentative and the customer may refer to the frequency or spectralcontent of each one's voice. The tone of voice may also refer to theamplitude or volume of each voice. Thus, the processing element 22 mayperform mathematical or signal processing operations such as Fouriertransforms, pulse coding, and the like in order to determine variationsin the frequency, the amplitude, or both of each voice. The processingelement 22 may repeatedly generate voice prints and compare them withalready stored voice prints, as discussed above, to identify the voiceof the representative and the voice of the customer. The processingelement 22 may further utilize the identities of the voice prints todetermine the tone of voice for the representative and the tone of voicefor the customer on an ongoing basis for the entire conversation. Thetone of voice of each person may be recorded in the memory element 20 asone or more values representing the tone of voice for each of aplurality of timestamps. The tone of voice may be recorded at a givenrate, such as 1-10 samples per second. Thus, the memory element 20 mayinclude a first series of tone of voice values for the representativeand a second series of tone of voice values for the customer. Theprocessing element 22 may also determine a first average tone of voicevalue for the representative and a second average tone of voice valuefor the customer.

Referring to step 110, whether the representative changed his tone ofvoice in response to a change in tone of voice of the customer may bedetermined. During the conversation, the customer may speak for a turnand then the representative may speak for a turn. The representative mayrespond to a question from the customer or may make a statementfollowing a statement from the customer. The processing element 22 maydetermine whether the customer changed his tone of voice during his turnand whether the representative changed his tone of voice in response. Invarious embodiments, the processing element 22 may determine eachoccurrence when the customer's tone of voice value is above a firstthreshold, such as 10% greater than his average tone of voice value. Theprocessing element 22 may further determine whether the tone of voicevalue for the representative increases above a second threshold, such asa 10% increase greater than his average tone of voice value, within afirst time period afterward, such as 10 seconds.

Referring to steps 111-113, a second score that varies according towhether the representative changed his tone of voice in response to achange in tone of voice of the customer may be generated or calculated.For example, the second score may have an initial value, such as 0 or100. The processing element 22 may increase the second score during theconversation when the representative does not change his tone of voicein response to a change in tone of voice of the customer. This mayindicate that the representative has remained calm during a tense orconfrontational moment of the conversation. Likewise, the processingelement 22 may decrease the second score during the conversation whenthe representative changes his tone of voice in response to a change intone of voice of the customer—perhaps indicating that the representativewas unable to remain calm when the customer got agitated.

Referring to step 114, a response time between when the customer stopstalking and the representative starts talking may be determined orcalculated. The processing element 22 may repeatedly generate voiceprints and compare them with already stored voice prints, as discussedabove, to identify the voice of the representative and the voice of thecustomer. The processing element 22 may also assume that the voice whichdoes not match a voice print is the customer's. The processing element22 may further determine a response time which is related to the periodof time that elapses between when the customer stops talking and therepresentative starts talking. In certain embodiments, the processingelement 22 may start a timer at the end of every word spoken by thecustomer. The timer may stop when the next word is spoken. If the nextword is spoken by the representative, then the processing element 22 mayrecord the value of the timer—which would correspond to the responsetime. In some cases, the processing element 22 may determine that therepresentative and the customer are speaking at the same time.

Referring to steps 115 and 116, a third score that varies according tothe response time may be generated or calculated. For example, the thirdscore may have an initial value, such as 100. In various embodiments,there may be a window of time, say between a lower threshold of 1 secondand an upper threshold of 5 seconds, during which it is consideredpolite for the representative to respond to the customer. If theresponse time is less than the lower threshold or the representative andthe customer are speaking simultaneously, then the representative may beinterrupting the customer. If the response time is greater than theupper threshold, then the representative may be considered to be keepingthe customer waiting. The processing element 22 may record all of theoccurrences when the response time was outside of the window and thetimes during the conversation when they occurred. In an exemplaryimplementation, the third score may not change as long the response timeis within the window. But, the processing element 22 may decrease thethird score for every occurrence when the response time is less than thelower threshold or greater than the upper threshold.

Referring to step 117, an evaluation may be presented to therepresentative after the conversation is over. The processing element 22may generate a total score, which may be a combination of the first,second, and third scores, such as the sum of the three or the average ofthe three that are communicated to the display 18. In addition orinstead, the computing device 10 may present the representative with thethree individual scores. Furthermore, the computing device 10 maycommunicate the evaluation to the display 18. The evaluation may includea list of both the positive words or phrases and the negative words andphrases used by the representative. The evaluation may also include alist of occurrences when the representative changed his tone of voiceand the times during the conversation when they occurred. The evaluationmay further include a list of occurrences when the representative didnot respond to the customer during the window of time for a properresponse and the times during the conversation when they occurred. Theevaluation may additionally include suggestions for improvement orbehavioral changes, if needed.

Exemplary Software Application

FIG. 3 illustrates at least a portion of the components of an exemplarysoftware application 24 for providing an evaluation to a customerservice representative regarding his performance during an interactionwith a customer. The software application 24 may be implemented during aphone call between the customer and the representative. The softwareapplication 24 may be generally executed by the computing device 10 andmay broadly comprise a voice print generator 26, a speech recognitioncomponent 28, a transcript comparison component 30, a first scoregenerator 32, a tone of voice determination component 34, a second scoregenerator 36, a response time determination component 38, a third scoregenerator 40, and/or an evaluation generator 42.

The voice print generator 26 may receive audio communication from amicrophone to which the representative has access or from thecommunication network 12. The audio communication may include anelectronic signal that is digitized and filtered to create a data streamwhich corresponds to speech from the representative. The representativemay speak a plurality of words or phrases or a series of sounds whichare analyzed by the voice print generator 26 to create a voice print,template, and/or model that is stored in the memory element 20 andaccessed by the software application 24. The voice print generator 26may generate a spectrogram or utilize the short-time Fourier transformto create the voice print. The voice print may be used to identify therepresentative.

In various embodiments, during the conversation, the voice printgenerator 26 may also successively or repeatedly generate a spectrogramor utilize the short-time Fourier transform to create a plurality ofvoice prints, each voice print derived from a period of time, such as0.5-1 seconds. The voice print generator 26 may compare thesuccessively-generated voice prints with the voice print of therepresentative to identify the voice of the current speaker during theconversation on an ongoing basis or as a function of time. Those voiceprints that match the voice print of the representative may beassociated with, identified, marked, or noted in the memory element 20as the voice of the representative. Those voice prints that do not matchthe voice print of the representative may be associated with,identified, marked, or noted in the memory element 20 as the voice ofthe customer. Alternatively, the voice print generator 26 maycommunicate the voice prints to the other components of the softwareapplication 24 to perform the comparison and identification.

The speech recognition component 28 may receive audio communication fromthe communication network 12. The audio communication may include anelectronic signal that is digitized and filtered to create a data streamwhich corresponds to the conversation between the representative and thecustomer. The speech recognition component 28 may utilize techniquessuch as hidden Markov models, dynamic time warping, neural networking,or the like, or combinations thereof in order to convert the data streamto text. The speech recognition component 28 may receive or access theidentified voice prints generated by the voice print generator 26. Thespeech recognition component 28 may also timestamp the text so that eachword is associated with a time of the conversation. The speechrecognition component 28 may match each word of the conversation withone or more identified voice prints so that it may determine whichperson spoke each word. Thus, the speech recognition component 28 maygenerate a representative transcript of the conversation which includesthose words of the text that are spoken by the representative. Thespeech recognition component 28 may also generate a customer transcriptincluding words of the text that are spoken by the customer.

The transcript comparison component 30 may compare the representativetranscript in an ongoing process throughout the conversation with a listof positive words or phrases and a list of negative words or phrases.The positive words or phrases may include language that is preferred forinteracting with customers, such as correct grammar, common courtesies,and/or proper etiquette. The negative words or phrases may includelanguage that is considered to be incorrect grammar, slang, and/orobscenities. The transcript comparison component 30 may determine apositive count corresponding to a number of occurrences or instanceswhen the words of the representative transcript match one or morepositive words. The transcript comparison component 30 may alsodetermine a negative count corresponding to a number of occurrences orinstances when the words of the representative transcript match one ormore negative words. The transcript comparison component 30 may alsostore in the memory element 20 all of the positive words used by therepresentative and the number of occurrences of each usage, as well asthe negative words used by the representative, and the number ofoccurrences of each usage. Alternatively, the transcript comparisoncomponent 30 may mark the positive words and negative words in therepresentative transcript which is stored in the memory element 20.

The first score generator 32 may generate a first score which variesaccording to the usage of positive words and negative words by therepresentative. For example, the first score may have an initial value,such as 0 or 100. The first score generator 32 may increase the firstscore based upon the positive count from the transcript comparisoncomponent 30. Likewise, the first score generator 32 may decrease thefirst score based upon the negative count from the transcript comparisoncomponent 30.

The tone of voice determination component 34 may determine a tone ofvoice for the representative and determine a tone of voice for thecustomer. The tone of voice of the representative and the customer mayrefer to the frequency or spectral content of each one's voice. The toneof voice may also refer to the amplitude or volume of each voice. Thus,the tone of voice determination component 34 may perform mathematical orsignal processing operations such as Fourier transforms, pulse coding,and the like in order to determine variations in the frequency, theamplitude, or both of each voice. The tone of voice determinationcomponent 34 may receive or access the identified voice prints generatedby the voice print generator 26. The tone of voice determinationcomponent 34 may further utilize the identified voice prints todetermine the tone of voice for the representative and the tone of voicefor the customer on an ongoing basis for the entire conversation. Thetone of voice of each person may be recorded in the memory element 20 asone or more values representing the tone of voice for each of aplurality of timestamps. The tone of voice may be recorded at a givenrate, such as 10 samples per second. Thus, the memory element 20 mayinclude a first series of tone of voice values for the representativeand a second series of tone of voice values for the customer. The toneof voice determination component 34 may also determine a first averagetone of voice value for the representative and a second average tone ofvoice value for the customer. In addition, the tone of voicedetermination component 34 may match, or otherwise associate, the toneof voice of the representative with the words spoken by therepresentative. For example, each word of the conversation spoken by therepresentative may be associated with an average, or maximum, tone ofvoice value that was recorded for the particular word of theconversation. The tone of voice determination component 34 may performthe same operation for the tone of voice of the customer.

In various embodiments, the tone of voice determination component 34 maydetermine each occurrence when the customer's tone of voice value isabove a first threshold, such as 10% greater than his average tone ofvoice value. The tone of voice determination component 34 may furtherdetermine, for each occurrence, whether the tone of voice value for therepresentative increases above a second threshold, such as a 10%increase greater than his average tone of voice value, within a firsttime period afterward, such as 10 seconds.

The second score generator 36 may generate a second score which variesaccording to whether the representative changed his tone of voice inresponse to a change in tone of voice of the customer. For example, thesecond score may have an initial value, such as 0 or 100. The secondscore generator 36 may increase the second score during the conversationwhen the representative does not change his tone of voice in response toa change in tone of voice of the customer. This may indicate that therepresentative has remained calm during a tense or confrontationalmoment of the conversation. Likewise, the second score generator 36 maydecrease the second score during the conversation when therepresentative changes his tone of voice in response to a change in toneof voice of the customer—perhaps indicating that the representative wasunable to remain calm when the customer got agitated.

The response time determination component 38 may determine a responsetime which is related to the period of time that elapses between whenthe customer stops talking and the representative starts talking. Duringthe conversation, the response time determination component 38 mayreceive or access the identified voice prints generated by the voiceprint generator 26. The response time determination component 38 mayutilize the identified voice prints to determine when the representativeis speaking and when the customer is speaking. In certain embodiments,the response time determination component 38 may start a timer at theend of every word spoken by the customer. The timer may stop when thenext word is spoken. If the next word is spoken by the representative,then the response time determination component 38 may record the valueof the timer—which corresponds to the response time. In some cases, theresponse time determination component 38 may determine that therepresentative and the customer are speaking at the same time.

The third score generator 40 may generate a third score that variesaccording to the response time. For example, the third score may have aninitial value, such as 100. In various embodiments, there may be awindow of time, say between a lower threshold of 1 second and an upperthreshold of 5 seconds, during which it is considered polite for therepresentative to respond to the customer. If the response time is lessthan the lower threshold or the representative and the customer arespeaking simultaneously, then the representative may be interrupting thecustomer. If the response time is greater than the upper threshold, thenthe representative may be considered to be keeping the customer waiting.The third score generator 40 may record all of the occurrences when theresponse time was outside of the window and the times during theconversation when they occurred. In an exemplary implementation, thethird score may not change as long as the response time is within thewindow. But, the third score generator 40 may decrease the third scorefor every occurrence when the response time is less than the lowerthreshold or greater than the upper threshold.

The evaluation generator 42 may generate an evaluation of therepresentative's performance after the conversation has ended. Theevaluation generator 42 may generate a total score, which may be acombination of the first, second, and third scores, such as the sum ofthe three or the average of the three that are communicated to thedisplay 18. In addition or instead, the evaluation generator 42 maypresent the representative with the three individual scores.Furthermore, the evaluation generator 42 may communicate the evaluationto the display 18. The evaluation may include a list of both thepositive words or phrases and the negative words and phrases used by therepresentative. The evaluation may also include a list of occurrenceswhen the representative changed his tone of voice and the times duringthe conversation when they occurred. The evaluation may further includea list of occurrences when the representative did not respond to thecustomer during the window of time for a proper response and the timesduring the conversation when they occurred. The evaluation mayadditionally include suggestions for improvement or behavioral changes,if needed.

Exemplary Computer-Implemented Method for Providing an Evaluation to aCustomer Service Representative Regarding his Performance During anInteraction with a Customer

In a first aspect, a computer-implemented method for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Themethod may include, via one or more processors: (1) receiving adigitized data stream corresponding to a spoken conversation between acustomer and a representative; (2) converting the data stream to a textstream; (3) generating a representative transcript that includes thewords from the text stream that are spoken by the representative; (4)comparing the representative transcript with a plurality of positivewords and a plurality of negative words; and/or (5) generating a scorethat varies according to the occurrence of each word spoken by therepresentative that matches one of the positive words and the occurrenceof each word spoken by the representative that matches one of thenegative words. The method may include additional, fewer, or alternativeactions, including those discussed elsewhere herein.

For instance, the method may include, via one or more processors:increasing the score corresponding to usage of positive words;decreasing the score corresponding to usage of negative words;generating a plurality of voice prints, each voice print derived fromone of a plurality of periods of time during the conversation; comparingeach voice print with a voice print of the representative to determinean identity of the voice print; indicating a first set of voice printsthat are associated with the representative and a second set of voiceprints that are associated with the customer; matching the first set ofvoice prints with words from the text stream that are spoken by therepresentative; and/or presenting the score, a list of words from therepresentative transcript that match one or more positive words, and alist of words from the representative transcript that match one or morenegative words on a display.

Exemplary Network Computing Device for Providing an Evaluation to aCustomer Service Representative Regarding his Performance During anInteraction with a Customer

In another aspect, a computing device for providing an evaluation to acustomer service representative regarding his performance during aninteraction with a customer may be provided. The computing device mayinclude a memory element and a processing element. The processingelement may be electronically coupled to the memory element. Theprocessing element may be configured to receive a digitized data streamcorresponding to a spoken conversation between a customer and arepresentative; convert the data stream to a text stream; generate arepresentative transcript that includes the words from the text streamthat are spoken by the representative; compare the representativetranscript with a plurality of positive words and a plurality ofnegative words; and/or generate a score that varies according to theoccurrence of each word spoken by the representative that matches one ofthe positive words and the occurrence of each word spoken by therepresentative that matches one of the negative words. The computingdevice may include additional, fewer, or alternate components and/orfunctionality, including that discussed elsewhere herein.

For instance, the processing element may be further configured to:increase the score corresponding to usage of positive words; decreasethe score corresponding to usage of negative words; generate a pluralityof voice prints, each voice print derived from one of a plurality ofperiods of time during the conversation; compare each voice print with avoice print of the representative to determine an identity of the voiceprint; indicate a first set of voice prints that are associated with therepresentative and a second set of voice prints that are associated withthe customer; match the first set of voice prints with words from thetext stream that are spoken by the representative; and/or present thescore, a list of words from the representative transcript that match oneor more positive word, and a list of words from the representativetranscript that match one or more negative word on a display.

Exemplary Software Application for Providing an Evaluation to a CustomerService Representative Regarding his Performance During an Interactionwith a Customer

In yet another aspect, a software application for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Thesoftware application may comprise a speech recognition component, atranscript comparison component, and/or a score generator. The speechrecognition component may receive a digitized data stream correspondingto a spoken conversation between a customer and a representative. Thespeech recognition component may be configured to convert the datastream to a text stream and generate a representative transcript thatincludes the words from the text stream that are spoken by therepresentative. The transcript comparison component may receive therepresentative transcript. The transcript comparison component may beconfigured to compare the representative transcript with a plurality ofpositive words and a plurality of negative words; determine a positivecount corresponding to a number of occurrences when the words of therepresentative transcript match one or more positive words; and/ordetermine a negative count corresponding to a number of occurrences whenthe words of the representative transcript match one or more negativewords. The score generator may receive the positive count and thenegative count. The score generator may be configured to generate ascore which varies based upon the positive count and the negative count.The software application may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

For instance, the software application may further comprise a voiceprint generator which receives the digitized data stream and may beconfigured to generate a plurality of voice prints, each voice printderived from one of a plurality of periods of time during theconversation, compare each voice print with a voice print of therepresentative to determine an identity of the voice print; associatethe voice prints that match the voice print of the representative withthe voice of the representative; and/or associate the voice prints thatdo not match the voice print of the representative with the voice of thecustomer. The software application may additionally comprise anevaluation generator which receives the score and is configured topresent the score, a list of words from the representative transcriptthat match one or more positive words, and/or a list of words from therepresentative transcript that match one or more negative words on adisplay. In addition, the score generator may be further configured toincrease the score corresponding to the positive count and decrease thescore corresponding to the negative count. The components may becomputer-readable or computer-executable instructions, computerapplications, and/or computer-executable instruction modules stored onnon-transitory computer-readable media or medium.

Exemplary Computer-Readable Medium for Providing an Evaluation to aCustomer Service Representative Regarding his Performance During anInteraction with a Customer

In yet another aspect, a computer-readable medium for providing anevaluation to a customer service representative regarding hisperformance during an interaction with a customer may be provided. Thecomputer-readable medium may include an executable program storedthereon, wherein the program instructs a processing element of acomputing device to perform the following steps: (1) receiving adigitized data stream corresponding to a spoken conversation between acustomer and a representative; (2) converting the data stream to a textstream; (3) generating a representative transcript that includes thewords from the text stream that are spoken by the representative; (4)comparing the representative transcript with a plurality of positivewords and a plurality of negative words; and/or (5) generating a scorethat varies according to the occurrence of each word spoken by therepresentative that matches one of the positive words and the occurrenceof each word spoken by the representative that matches one of thenegative words. The program stored on the computer-readable medium mayinstruct the processing element to perform additional, fewer, oralternative actions, including those discussed elsewhere herein.

For instance, the program may instruct the processing element to:increase the score corresponding to usage of positive words; decreasethe score corresponding to usage of negative words; generate a pluralityof voice prints, each voice print derived from one of a plurality ofperiods of time during the conversation; compare each voice print with avoice print of the representative to determine an identity of the voiceprint; indicate a first set of voice prints that are associated with therepresentative and a second set of voice prints that are associated withthe customer; match the first set of voice prints with words from thetext stream that are spoken by the representative; and/or present thescore, a list of words from the representative transcript that match oneor more positive words, and a list of words from the representativetranscript that match one or more negative words on a display.

Exemplary Feedback & Quality Assurance

A tool or computer system may be configured to provide for an objectiveand/or more accurate review of customer-call center representativetelephone calls. The tool or computer system may provide (1) immediateassociate feedback enabled by voice recognition software; (2) qualityassurance processes that include new, more comprehensive call data;and/or (3) systematic messaging to reinforce desired behaviors, basedupon vocal metrics.

Voice recognition technology may be used to gather an increased amountof data, looking for particular words and tones of voice that areassumed to be representative of exemplary associate behaviors. Certainwords or phrases may be considered to be particularly appropriate (forexample, drawing from a library of common courtesies, or from desiredword tracks for certain transactions). Certain words or phrases may alsobe considered particularly inappropriate. Certain etiquette protocolsmay also be detected (for example, whether an associate interrupts acustomer). The tone of voice may be detected (for both associates andcustomers).

All of these factors may then be correlated to a scoring—with certainwords, phrases, points of etiquette considered to be particularlypositive or negative. In the aggregate, this scoring could be used toprovide general feedback regarding the assumed quality of individualcalls and groups of calls (either for individual associates, or sets ofassociates). The specifically detected words, phrases, and points ofetiquette may also provide the basis for immediate associate feedback.

For example, at the conclusion of a call, the associate may receiveon-screen messaging that reinforces aspects of the conversation thatscored well, as well as a suggestion for alternative phrasing whenaspects of the conversation scored poorly. Based upon tones of voicedetected, the associate may also receive positive feedback about stayingcalm during a tense call (for example, by evaluating the tone of voiceof the customer versus the tone of voice of the associate).

Feedback about a telephone call or text interaction with a customer maybe provided to the representative during or after a customerinteraction. A pop-up window on a computer display screen may provideshort bullets of encouragement, feedback, and/or areas of opportunityfor improved customer service.

In one aspect, a computer-implemented method of providing customerservice feedback and quality assurance may be provided. The method mayinclude (1) monitoring, via one or more processors, a communicationstream (and/or associated voice or text communication data) during acustomer interaction between a customer and a representative, theinteraction being a telephone call or a texting interaction; (2)analyzing, via the one or more processors, the communication stream todetermine (i) a word choice by, and/or (ii) a tone of voice of, therepresentative during the interaction; (3) generating, via the one ormore processors, feedback for the representative regarding the customerinteraction based upon the (i) word choice, and/or (ii) tone of voicedetermined; and/or (4) providing, via the one or more processors, thefeedback to the representative during or after the customer interaction,such as displaying bullet points on a computer display screen, tofacilitate providing objective feedback to the representative to enhancethe quality of future customer experiences.

The computer-implemented method may further include (i) analyzing, viathe one or more processors, the communication stream to determine aresponse time of the representative during the interaction; (ii)generating, via the one or more processors, feedback for therepresentative based upon the response time; and/or (iii) providing, viathe one or more processors, the feedback based upon response time to therepresentative during or after the customer interaction. The method mayinclude generating, via the one or more processors, one or more scoresbased upon the word choice, tone of voice, and/or response time analysisor determinations; and/or causing, via the one or more processors, theone or more scores to be displayed on a computer screen during or aftera customer interaction for the representative's review to provideobjective feedback to the representative and enhance future customerexperiences and/or service. Generating, via the one or more processors,feedback for the representative regarding the customer interaction basedupon the (i) word choice, and/or (ii) tone of voice determined mayinclude analyzing the communication stream or data to determine certainwords, phrases, and/or points of etiquette used by the representativeduring the customer interaction, and/or comparing the certain words,phrases, and/or points of etiquette determined with words, phrases,and/or points of etiquette stored in a memory unit or data structure toidentify positive or negative words, phrases, and/or points of etiquetteused by the representative. The method may include additional, less, oralternate actions, including those discussed elsewhere herein, and/ormay be implemented via one or more processors and/or viacomputer-executable instructions stored on a non-transitorycomputer-readable medium.

In another aspect, a computer-implemented method of providing customerservice feedback and quality assurance may be provided. The method mayinclude (1) generating or collecting, via one or more processors,communication data (or communication data stream) during (or associatedwith) a customer interaction between a customer and a representative,the interaction being a telephone call, or an audible or textconversation; (2) storing, via the one or more processors, thecommunication data (or communication data stream) in a memory unit; (3)analyzing, via the one or more processors, the communication data (orcommunication data stream) either in real-time or by accessing the datastored in the memory unit, to determine (i) one or more word choices by,and/or (ii) one or more tones of voice of, the representative during thecustomer interaction; (4) generating, via the one or more processors,feedback based upon the one or more word choices or tones of voicedetermined from analysis of the communication data (or communicationstream); and/or (5) providing, via the one or more processors, thefeedback to the representative during or after the interaction basedupon (i) the one or more word choices and/or (ii) one or more tones ofvoice determined from computer analysis of the communication data(and/or communication stream), such as displaying bullet points on acomputer display screen, to facilitate providing objective feedback tothe representative to enhance the quality of future customerexperiences.

The method may include analyzing the communication data (and/orcommunication stream), via the one or more processors, to determine oneor more response times of the representative during the interaction;generating, via the one or more processors, feedback for therepresentative based upon the one or more response times; and/orproviding, via the one or more processors, the feedback based upon theone or more response times to the representative during or after thecustomer interaction based upon the response time.

The method may include generating, via the one or more processors, oneor more scores based upon the word choice, tone of voice, and/orresponse time analysis or determinations; and causing, via the one ormore processors, the one or more scores to be displayed on a computerscreen during or after a customer interaction for representative reviewto provide objective feedback to the representative and enhance futurecustomer experiences and/or service.

Generating, via the one or more processors, feedback for therepresentative regarding the customer interaction based upon the (i)word choice, and/or (ii) tone of voice determined may include analyzingthe communication data or stream to determine certain words, phrases,and/or points of etiquette used by the representative during thecustomer interaction, and/or comparing the certain words, phrase, and/orpoints of etiquette determined with pre-determined words, phrases,and/or points of etiquette stored in a memory unit or data structure toidentify positive or negative words, phrases, and/or points of etiquetteused by the representative. The method may include additional, less, oralternate actions, including those discussed elsewhere herein, and/ormay be implemented via one or more processors and/or viacomputer-executable instructions stored on a non-transitorycomputer-readable medium.

Exemplary Computer Systems

In one aspect, a computer system configured to provide customer servicefeedback and quality assurance may be provided. The computer system mayinclude one or more processors configured to: (1) monitor acommunication stream (and/or associated data) during a customerinteraction between a customer and a representative, the interactionbeing a telephone call or a texting interaction; (2) analyze thecommunication stream (and/or associated data) to determine a word choiceby, and/or a tone of voice of, the representative during theinteraction; (3) generate feedback based upon the word choice and/ortone of voice determined from computer analysis of the communicationstream (and/or associated data); and/or (4) provide the feedback basedupon the word choice and/or tone of voice to the representative duringor after the interaction, such as displaying bullet points on a computerdisplay screen, to facilitate providing objective feedback to therepresentative to enhance the quality of future customer experiences.The computer system and/or processors may be configured with additional,less, or alternate functionality, including that discussed elsewhereherein.

For instance, the one or more processors may be further configured to:analyze the communication stream to determine one or more response timesof the representative during the interaction; and/or provide feedbackbased upon the one or more response times to the representative duringor after the customer interaction. The one or more processors furtherconfigured to: generate one or more scores based upon the word choice,tone of voice, or response time analysis or determinations; and/or causethe one or more scores to be displayed on a computer screen during orafter a customer interaction for representative review to provideobjective feedback to the representative and enhance future customerexperiences and/or service.

Generating, via the one or more processors, feedback for therepresentative regarding the customer interaction based upon the (i)word choice, and/or (ii) tone of voice determined may include analyzingthe communication stream or data to determine certain words, phrases,and/or points of etiquette used by the representative during thecustomer interaction, and/or comparing the certain words, phrases,and/or points of etiquette determined with predetermined words, phrases,and/or points of etiquette stored in a memory unit or data structure toidentify positive or negative words, phrases, and/or points of etiquetteused by the representative.

In another aspect, a computer system configured to provide customerservice feedback and quality assurance may be provided. The computersystem may include one or more processors configured to: (1) generate orcollect communication data (or communication data stream) during (orassociated with) a customer interaction between a customer and arepresentative, the interaction being a telephone call, or an audible ortext conversation; (2) store the communication data (or communicationdata stream) in a memory unit; (3) analyze the communication data (orcommunication data stream) either in real-time or by accessing the datastored in the memory unit, to determine (i) one or more word choices by,and/or (ii) one or more tones of voice of, the representative during thecustomer interaction; (4) generate feedback based upon the one or moreword choices or tones of voice determined from analysis of thecommunication data (or communication stream); and/or (5) provide thefeedback to the representative during or after the interaction basedupon (i) the one or more word choice and/or (ii) one or more tones ofvoice determined from computer analysis of the communication data(and/or communication stream), such as displaying bullet points on acomputer display screen, to facilitate providing objective feedback tothe representative to enhance the quality of future customerexperiences. The computer system and/or processor(s) may includeadditional, less, or alternate functionality or capability, includingthat discussed elsewhere herein.

For instance, the one or more processors may be configured to: analyzethe communication data (and/or communication stream) to determine one ormore response times of the representative during the interaction;generate feedback for the representative based upon the one or moreresponse times determined; and/or provide, present, or display thefeedback based upon the one or more response times to the representativeduring or after the customer interaction based upon the response time.

The one or more processors may further be configured to: generate one ormore scores based upon the one or more word choices, one or more tonesof voice, and/or one or more response times determined; and/or causing,via the one or more processors, the one or more scores to be displayedon a computer screen during or after a customer interaction forrepresentative review to provide objective feedback to therepresentative and enhance future customer experiences and/or service.

Generating, via the one or more processors, feedback for therepresentative regarding the customer interaction based upon the (i) oneor more word choices, and/or (ii) one or more tones of voice determinedmay include analyzing the communication data or stream to determinecertain words, phrases, and/or points of etiquette used by therepresentative during the customer interaction, and/or comparing thecertain words, phrase, and/or points of etiquette determined withpre-determined words, phrases, and/or points of etiquette stored in amemory unit or data structure to identify positive or negative words,phrases, and/or points of etiquette used by the representative.

ADDITIONAL CONSIDERATIONS

In this description, references to “one embodiment”, “an embodiment”, or“embodiments” mean that the feature or features being referred to areincluded in at least one embodiment of the technology. Separatereferences to “one embodiment”, “an embodiment”, or “embodiments” inthis description do not necessarily refer to the same embodiment and arealso not mutually exclusive unless so stated and/or except as will bereadily apparent to those skilled in the art from the description. Forexample, a feature, structure, act, etc. described in one embodiment mayalso be included in other embodiments, but is not necessarily included.Thus, the current technology can include a variety of combinationsand/or integrations of the embodiments described herein.

Although the present application sets forth a detailed description ofnumerous different embodiments, it should be understood that the legalscope of the description is defined by the words of the claims set forthat the end of this patent and equivalents. The detailed description isto be construed as exemplary only and does not describe every possibleembodiment since describing every possible embodiment would beimpractical. Numerous alternative embodiments may be implemented, usingeither current technology or technology developed after the filing dateof this patent, which would still fall within the scope of the claims.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Certain embodiments are described herein as including logic or a numberof routines, subroutines, applications, or instructions. These mayconstitute either software (e.g., code embodied on a machine-readablemedium or in a transmission signal) or hardware. In hardware, theroutines, etc., are tangible units capable of performing certainoperations and may be configured or arranged in a certain manner. Inexample embodiments, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) ascomputer hardware that operates to perform certain operations asdescribed herein.

In various embodiments, computer hardware, such as a processing element,may be implemented as special purpose or as general purpose. Forexample, the processing element may comprise dedicated circuitry orlogic that is permanently configured, such as an application-specificintegrated circuit (ASIC), or indefinitely configured, such as an FPGA,to perform certain operations. The processing element may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement the processingelement as special purpose, in dedicated and permanently configuredcircuitry, or as general purpose (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “processing element” or equivalents should beunderstood to encompass a tangible entity, be that an entity that isphysically constructed, permanently configured (e.g., hardwired), ortemporarily configured (e.g., programmed) to operate in a certain manneror to perform certain operations described herein. Consideringembodiments in which the processing element is temporarily configured(e.g., programmed), each of the processing elements need not beconfigured or instantiated at any one instance in time. For example,where the processing element comprises a general-purpose processorconfigured using software, the general-purpose processor may beconfigured as respective different processing elements at differenttimes. Software may accordingly configure the processing element toconstitute a particular hardware configuration at one instance of timeand to constitute a different hardware configuration at a differentinstance of time.

Computer hardware components, such as communication elements, memoryelements, processing elements, and the like, may provide information to,and receive information from, other computer hardware components.Accordingly, the described computer hardware components may be regardedas being communicatively coupled. Where multiple of such computerhardware components exist contemporaneously, communications may beachieved through signal transmission (e.g., over appropriate circuitsand buses) that connect the computer hardware components. In embodimentsin which multiple computer hardware components are configured orinstantiated at different times, communications between such computerhardware components may be achieved, for example, through the storageand retrieval of information in memory structures to which the multiplecomputer hardware components have access. For example, one computerhardware component may perform an operation and store the output of thatoperation in a memory device to which it is communicatively coupled. Afurther computer hardware component may then, at a later time, accessthe memory device to retrieve and process the stored output. Computerhardware components may also initiate communications with input oroutput devices, and may operate on a resource (e.g., a collection ofinformation).

The various operations of example methods described herein may beperformed, at least partially, by one or more processing elements thatare temporarily configured (e.g., by software) or permanently configuredto perform the relevant operations. Whether temporarily or permanentlyconfigured, such processing elements may constitute processingelement-implemented modules that operate to perform one or moreoperations or functions. The modules referred to herein may, in someexample embodiments, comprise processing element-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processing element-implemented. For example, at least some ofthe operations of a method may be performed by one or more processingelements or processing element-implemented hardware modules. Theperformance of certain of the operations may be distributed among theone or more processing elements, not only residing within a singlemachine, but deployed across a number of machines. In some exampleembodiments, the processing elements may be located in a single location(e.g., within a home environment, an office environment or as a serverfarm), while in other embodiments the processing elements may bedistributed across a number of locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer with a processing element andother computer hardware components) that manipulates or transforms datarepresented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s).

Although the invention has been described with reference to theembodiments illustrated in the attached drawing figures, it is notedthat equivalents may be employed and substitutions made herein withoutdeparting from the scope of the invention as recited in the claims.

Having thus described various embodiments of the invention, what isclaimed as new and desired to be protected by Letters Patent includesthe following: 1-20. (canceled)
 21. A computer-implemented method forevaluating performance of a call associate during an interaction with anindividual, the individual being a customer or a potential customer, thecomputer-implemented method comprising: analyzing, via one or moreprocessors using voice recognition, information derived from anelectronic representation of an oral conversation involving the callassociate and the individual to identify instances of use by the callassociate of positive words and instances of use by the call associateof negative words; generating, via the one or more processors, a firstevaluation of the instances of use by the call associate of positivewords and a second evaluation of the instances of use by the callassociate of negative words; and providing a first visual indicatorcorresponding to the first evaluation and a second visual indicatorcorresponding to the second evaluation for display on a device asfeedback regarding the performance of the call associate.
 22. Thecomputer-implemented method of claim 21, further comprising: analyzing,via the one or more processors, the information to identify instances ofuse by the call associate of words designated for a particulartransaction; generating, via the one or more processors, a thirdevaluation of the instances of use by the call associate of wordsdesignated for a particular transaction; and providing a third visualindicator corresponding to the third evaluation for display on thedevice as feedback regarding the performance of the call associate. 23.The computer-implemented method of claim 21, wherein the firstevaluation is a first score and the second evaluation is a second score.24. The computer-implemented method of claim 21, wherein the firstvisual indicator and the second visual indicator are provided fordisplay in real-time during the conversation.
 25. Thecomputer-implemented method of claim 21, wherein the first visualindicator and the second visual indicator are provided for display afterthe conclusion of the conversation.
 26. The computer-implemented methodof claim 21, further comprising providing on-screen messaging fordisplay on a device associated with the call associate to reinforce atleast one aspect of the conversation corresponding to a favorableevaluation.
 27. The computer-implemented method of claim 21, wherein thefirst visual indicator is a numeric representation of usage of positivewords and the second visual indicator is a numeric representation ofusage of negative words.
 28. The computer-implemented method of claim22, wherein the third visual indicator is a numeric representation ofusage of designated for a particular transaction.
 29. A computing devicefor evaluating performance of a call associate during an interactionwith an individual, the individual being a customer or a potentialcustomer, the computing device comprising: a processing element; and amemory element including instructions that when executed by theprocessing element cause the processing element to: analyze using voicerecognition, information derived from an electronic representation of anoral conversation involving the call associate and the individual toidentify instances of use by the call associate of positive words andinstances of use by the call associate of negative words; generate afirst evaluation of the instances of use by the call associate ofpositive words and a second evaluation of the instances of use by thecall associate of negative words; and provide a first visual indicatorcorresponding to the first evaluation and a second visual indicatorcorresponding to the second evaluation for display on a device asfeedback regarding the performance of the call associate.
 30. Thecomputing device of claim 29, wherein the instructions, when executed bythe processing element, further cause the processing element to: analyzethe information to identify instances of use by the call associate ofwords designated for a particular transaction; generate a thirdevaluation of the instances of use by the call associate of wordsdesignated for a particular transaction; and provide a third visualindicator corresponding to the third evaluation for display on thedevice as feedback regarding the performance of the call associate. 31.The computing device of claim 29, wherein the first evaluation is afirst score and the second evaluation is a second score.
 32. Thecomputing device of claim 29, wherein the first visual indicator and thesecond visual indicator are provided for display in real-time during theconversation.
 33. The computing device of claim 29, wherein the firstvisual indicator and the second visual indicator are provided fordisplay after the conclusion of the conversation.
 34. The computingdevice of claim 29, wherein the instructions, when executed by theprocessing element, further cause the processing element to provideon-screen messaging for display on a device associated with the callassociate to reinforce at least one aspect of the conversationcorresponding to a favorable evaluation.
 35. The computing device ofclaim 29, wherein the first visual indicator is a numeric representationof usage of positive words and the second visual indicator is a numericrepresentation of usage of negative words.
 36. The computing device ofclaim 30, wherein the third visual indicator is a numeric representationof usage of designated for a particular transaction.
 37. Anon-transitory computer-readable medium with an executable programstored thereon for evaluating performance of a call associate during aninteraction with an individual, the individual being a customer or apotential customer, wherein the program instructs a processing elementof a computing device to perform the following: analyze using voicerecognition, information derived from an electronic representation of anoral conversation involving the call associate and the individual toidentify instances of use by the call associate of positive words andinstances of use by the call associate of negative words; generate afirst evaluation of the instances of use by the call associate ofpositive words and a second evaluation of the instances of use by thecall associate of negative words; and provide a first visual indicatorcorresponding to the first evaluation and a second visual indicatorcorresponding to the second evaluation for display on a device asfeedback regarding the performance of the call associate.
 38. Thenon-transitory computer-readable medium of claim 37, wherein the programfurther instructs the processing element to: analyze the information toidentify instances of use by the call associate of words designated fora particular transaction; generate a third evaluation of the instancesof use by the call associate of words designated for a particulartransaction; and provide a third visual indicator corresponding to thethird evaluation for display on the device as feedback regarding theperformance of the call associate.
 39. The non-transitorycomputer-readable medium of claim 37, wherein the first visual indicatorand the second visual indicator are provided for display in real-timeduring the conversation.
 40. The non-transitory computer-readable mediumof claim 37, wherein the first visual indicator is a numericrepresentation of usage of positive words and the second visualindicator is a numeric representation of usage of negative words.